Tianyu Chen’s research while affiliated with Concordia University and other places

Waste management systems have always been considered complex. Scholars have studied waste management mostly from a macro perspective for a long time, considering waste management policies as a fraction of this complex system. This study presents the causal variables and feedback relationships related to waste management from another perspective, from the inside of a policy, using the macroscopic ideas of Environment-based design (EBD) and the system dynamics pictorial representation. It clarifies the way in which policy acts on waste management systems and provides a new perspective for subsequent research on waste management policy.KeywordsPolicy modelEnvironment-based design (EBD)System dynamicsVariablesFeedback diagram

Existing data quality criteria often focus on the quality of the data itself while overlooking other aspects such as the relevance between data and downstream tasks. Furthermore, prior to data collection, policy-makers lack ground truths or labelled data, and are unable to filter data using quantitative criteria. To ensure the collection of reliable, necessary, and sufficient data for policy-making, this study derives a data-driven policy-making framework from Environment-based Design (EBD). Based on the framework, we present five qualitative criteria called RULER (Reliable, Uncoupled, Lifecycle, Environment, Relevant) to evaluate and filter data for data-driven waste management and policy-marking. A case study from Beijing, China shows how to apply these criteria, through which a relatively reliable, sufficient, and necessary data list is given as result.